Document Type
Conference Paper
Publication Date
2012
DOI
10.1117/12.918935
Publication Title
Visual Information Processing XXI, Proceedings of SPIE 8399
Volume
8399
Pages
839902 (1-14)
Conference Name
SPIE Defense, Security, and Sensing, April 23-27, 2012, Baltimore Maryland
Abstract
Many applications require to register images within subpixel accuracy like computer vision especially super-resolution (SR) where the estimated subpixel shifts are very crucial in the reconstruction and restoration of SR images. In our work we have an optical sensor that is mounted on an unmanned airborne vehicle (UAV) and captures a set of images that contain sufficient overlapped area required to reconstruct a SR image. Due to the wind, The UAV may encounter rotational effects such as yaw, pitch and roll which can distort the acquired as well as processed images with shear, tilt or perspective distortions. In this paper we propose a hybrid algorithm to register these UAV images within subpixel accuracy to feed them in a SR reconstruction step. Our algorithm consists of two steps. The first step uses scale invariant feature transform (SIFT) to correct the distorted images. Because the resultant images are not registered to a subpixel precision, the second step registers the images using a fast Fourier transform (FFT) based method that is both efficient and robust to moderate noise and lens optical blur. Our FFT based method reduces the dimensionality of the Fourier matrix of the cross correlation and uses a forward and backward search in order to obtain an accurate estimation of the subpixel shifts. We discuss the relation between the dimensionality reduction factors and the image shifts as well as propose criteria that can be used to optimally select these factors. Finally, we compare the results of our approach to other subpixel techniques in terms of their efficiency and computational speed.
Rights
Copyright 2012 Society of Photo‑Optical Instrumentation Engineers (SPIE).
One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited.
Original Publication Citation
Yousef, A. H., Li, J., & Karim, M. (2012) Toward automatic subpixel registration of unmanned airborne vehicle images. In M. A. Neifeld & Amit Ashok (Eds.), Visual Information Processing XXI, Proceedings of SPIE 8399 (839902). SPIE of Bellingham, WA. https://doi.org/10.1117/12.918935
Repository Citation
Yousef, Amr Hussein; Li, Jiang; Karim, Mohammad; Neifeld, Mark Allen (Ed.); and Ashok, Amit (Ed.), "Toward Automatic Subpixel Registration of Unmanned Airborne Vehicle Images" (2012). Electrical & Computer Engineering Faculty Publications. 407.
https://digitalcommons.odu.edu/ece_fac_pubs/407
ORCID
0000-0003-0091-6986 (Li)